Selected article for: "impact spread and infected people"
Author: Leonid Sedov; Alexander Krasnochub; valentin polishchuk
Title: Modeling quarantine during epidemics by mass-testing with drones
  • Document date: 2020_4_20
    • ID: 98i0dwat_4
    Snippet: For the impact of our results on epidemic spread theory, we introduce an extension of the SIR model for epidemic development [KM27, HLM14] . The vanilla SIR model's transitions between its 3 compartments (or, states) S, I, R (Susceptible, Infected, Recovered resp.) are governed by the following differential equations dS/dt = -a*S*I, dI/dt = a*S*I -b*I, dR/dt = b*I where S, I, R stand for the number of susceptible, infected, recovered people resp......
    Document: For the impact of our results on epidemic spread theory, we introduce an extension of the SIR model for epidemic development [KM27, HLM14] . The vanilla SIR model's transitions between its 3 compartments (or, states) S, I, R (Susceptible, Infected, Recovered resp.) are governed by the following differential equations dS/dt = -a*S*I, dI/dt = a*S*I -b*I, dR/dt = b*I where S, I, R stand for the number of susceptible, infected, recovered people resp. as functions of the time t (the notation is slightly abused by identifying the numbers with the compartment names), and a, b are the parameters signifying the rates of the transfer between the states. The parameters are estimated from the clinical data; e.g., b=1/T where T is the average duration of the disease in a patient.

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